Carbon dioxide sequestration in cement kiln dust through miner carbonation

The feasibility of carbon sequestration in cement kiln dust (CKD) was investigated in a series of batch and column experiments conducted under ambient temperature and pressure conditions. The significance of this work is the demonstration that alkaline wastes, such as CKD, are highly reactive with carbon dioxide (CO2). In the presence of water, CKD can sequester greater than 80% of its theoretical capacity for carbon without any amendments or modifications to the waste. Other mineral carbonation technologies for carbon sequestration rely on the use of mined mineral feedstocks as the source of oxides. The mining, pre-processing and reaction conditions needed to create favorable carbonation kinetics all require significant additions of energy to the system. Therefore, their actual net reduction in CO2 is uncertain. Many suitable alkaline wastes are produced at sites that also generate significant quantities of CO2. While independently, the reduction in CO2 emissions from mineral carbonation in CKD is small (~13% of process related emissions), when this technology is applied to similar wastes of other industries, the collective net reduction in emissions may be significant. The technical investigations presented in this dissertation progress from proof of feasibility through examination of the extent of sequestration in core samples taken from an aged CKD waste pile, to more fundamental batch and microscopy studies which analyze the rates and mechanisms controlling mineral carbonation reactions in a variety of fresh CKD types. Finally, the scale of the system was increased to assess the sequestration efficiency under more pilot or field-scale conditions and to clarify the importance of particle-scale processes under more dynamic (flowing gas) conditions. A comprehensive set of material characterization methods, including thermal analysis, Xray diffraction, and X-ray fluorescence, were used to confirm extents of carbonation and to better elucidate those compositional factors controlling the reactions. The results of these studies show that the rate of carbonation in CKD is controlled by the extent of carbonation. With increased degrees of conversion, particle-scale processes such as intraparticle diffusion and CaCO3 micropore precipitation patterns begin to limit the rate and possibly the extent of the reactions. Rates may also be influenced by the nature of the oxides participating in the reaction, slowing when the free or unbound oxides are consumed and reaction conditions shift towards the consumption of less reactive Ca species. While microscale processes and composition affects appear to be important at later times, the overall degrees of carbonation observed in the wastes were significant (\u3e 80%), a majority of which occurs within the first 2 days of reaction. Under the operational conditions applied in this study, the degree of carbonation in CKD achieved in column-scale systems was comparable to those observed under ideal batch conditions. In addition, the similarity in sequestration performance among several different CKD waste types indicates that, aside from available oxide content, no compositional factors significantly hinder the ability of the waste to sequester CO2

The utility of continuous atmospheric measurements for identifying biospheric CO 2 flux variability

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95026/1/jgrd16859.pd

Sensitivity of inferred climate model skill to evaluation decisions: a case study using CMIP5 evapotranspiration

Confrontation of climate models with observationally-based reference datasets is widespread and integral to model development. These comparisons yield skill metrics quantifying the mismatch between simulated and reference values and also involve analyst choices, or meta-parameters, in structuring the analysis. Here, we systematically vary five such meta-parameters (reference dataset, spatial resolution, regridding approach, land mask, and time period) in evaluating evapotranspiration (ET) from eight CMIP5 models in a factorial design that yields 68 700 intercomparisons. The results show that while model–data comparisons can provide some feedback on overall model performance, model ranks are ambiguous and inferred model skill and rank are highly sensitive to the choice of meta-parameters for all models. This suggests that model skill and rank are best represented probabilistically rather than as scalar values. For this case study, the choice of reference dataset is found to have a dominant influence on inferred model skill, even larger than the choice of model itself. This is primarily due to large differences between reference datasets, indicating that further work in developing a community-accepted standard ET reference dataset is crucial in order to decrease ambiguity in model skill

Evaluation of simulated soil carbon dynamics in Arctic-Boreal ecosystems

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Huntzinger, D. N., Schaefer, K., Schwalm, C., Fisher, J. B., Hayes, D., Stofferahn, E., Carey, J., Michalak, A. M., Wei, Y., Jain, A. K., Kolus, H., Mao, J., Poulter, B., Shi, X., Tang, J., & Tian, H. Evaluation of simulated soil carbon dynamics in Arctic-Boreal ecosystems. Environmental Research Letters, 15(2), (2020): 025005, doi:10.1088/1748-9326/ab6784.Given the magnitude of soil carbon stocks in northern ecosystems, and the vulnerability of these stocks to climate warming, land surface models must accurately represent soil carbon dynamics in these regions. We evaluate soil carbon stocks and turnover rates, and the relationship between soil carbon loss with soil temperature and moisture, from an ensemble of eleven global land surface models. We focus on the region of NASA's Arctic-Boreal vulnerability experiment (ABoVE) in North America to inform data collection and model development efforts. Models exhibit an order of magnitude difference in estimates of current total soil carbon stocks, generally under- or overestimating the size of current soil carbon stocks by greater than 50 PgC. We find that a model's soil carbon stock at steady-state in 1901 is the prime driver of its soil carbon stock a hundred years later—overwhelming the effect of environmental forcing factors like climate. The greatest divergence between modeled and observed soil carbon stocks is in regions dominated by peat and permafrost soils, suggesting that models are failing to capture the frozen soil carbon dynamics of permafrost regions. Using a set of functional benchmarks to test the simulated relationship of soil respiration to both soil temperature and moisture, we find that although models capture the observed shape of the soil moisture response of respiration, almost half of the models examined show temperature sensitivities, or Q10 values, that are half of observed. Significantly, models that perform better against observational constraints of respiration or carbon stock size do not necessarily perform well in terms of their functional response to key climatic factors like changing temperature. This suggests that models may be arriving at the right result, but for the wrong reason. The results of this work can help to bridge the gap between data and models by both pointing to the need to constrain initial carbon pool sizes, as well as highlighting the importance of incorporating functional benchmarks into ongoing, mechanistic modeling activities such as those included in ABoVE.This work was supported by NASA'S Arctic Boreal Vulnerability Experiment (ABoVE; https://above.nasa.gov); NNN13D504T. Funding for the Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP; https://nacp.ornl.gov/MsTMIP.shtml) activity was provided through NASA ROSES Grant #NNX10AG01A. Data management support for preparing, documenting, and distributing model driver and output data was performed by the Modeling and Synthesis Thematic Data Center at Oak Ridge National Laboratory (MAST-DC; https://nacp.ornl.gov), with funding through NASA ROSES Grant #NNH10AN681. Finalized MsTMIP data products are archived at the ORNL DAAC (https://daac.ornl.gov). We also acknowledge the modeling groups that provided results to MsTMIP. The synthesis of site-level soil respiration, temperature, and moisture data reported in Carey et al 2016a, 2016b) was funded by the US Geological Survey (USGS) John Wesley Powell Center for Analysis and Synthesis Award G13AC00193. Additional support for that work was also provided by the USGS Land Carbon Program. JBF carried out the research at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. California Institute of Technology. Government sponsorship acknowledged

North American carbon dioxide sources and sinks: magnitude, attribution, and uncertainty

North America is both a source and sink of atmospheric carbon dioxide (CO2). Continental sources - such as fossil-fuel combustion in the US and deforestation in Mexico - and sinks - including most ecosystems, and particularly secondary forests - add and remove CO2 from the atmosphere, respectively. Photosynthesis converts CO2 into carbon as biomass, which is stored in vegetation, soils, and wood products. However, ecosystem sinks compensate for only similar to 35% of the continent's fossil-fuel-based CO2 emissions; North America therefore represents a net CO2 source. Estimating the magnitude of ecosystem sinks, even though the calculation is confounded by uncertainty as a result of individual inventory- and model-based alternatives, has improved through the use of a combined approach. Front Ecol Environ 2012; 10(10): 512-519, doi:10.1890/12006

The terrestrial biosphere model farm

Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901–2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges

Climate Science Special Report: Fourth National Climate Assessment (NCA4), Volume I

New observations and new research have increased our understanding of past, current, and future climate change since the Third U.S. National Climate Assessment (NCA3) was published in May 2014. This Climate Science Special Report (CSSR) is designed to capture that new information and build on the existing body of science in order to summarize the current state of knowledge and provide the scientific foundation for the Fourth National Climate Assessment (NCA4)

Comparative Expression Profiling of the Chlamydia trachomatis pmp Gene Family for Clinical and Reference Strains

Chlamydia trachomatis, an obligate intracellular pathogen, is a leading worldwide cause of ocular and urogenital diseases. Advances have been made in our understanding of the nine-member polymorphic membrane protein (Pmp) gene (pmp) family of C. trachomatis. However, there is only limited information on their biologic role, especially for biological variants (biovar) and clinical strains.We evaluated expression for pmps throughout development for reference strains E/Bour and L2/434, representing different biovars, and for clinical E and L2 strains. Immunoreactivity of patient sera to recombinant (r)Pmps was also determined. All pmps were expressed at two hours. pmpA had the lowest expression but was up-regulated at 12 h for all strains, indicating involvement in reticulate body development. For pmpD, expression peaked at 36 h. Additionally, 57.7% of sera from infected and 0% from uninfected adolescents were reactive to rPmpD (p = 0.001), suggesting a role in immunogenicity. pmpF had the highest expression levels for all clinical strains and L2/434 with differential expression of the pmpFE operon for the same strains. Sera were nonreactive to rPmpF despite immunoreactivity to rMOMP and rPmpD, suggesting that PmpF is not associated with humoral immune responses. pmpFE sequences for clinical strains were identical to those of the respective reference strains. We identified the putative pmpFE promoter, which was, surprisingly, 100% conserved for all strains. Analyses of ribosomal binding sites, RNase E, and hairpin structures suggested complex regulatory mechanism(s) for this >6 Kb operon.The dissimilar expression of the same pmp for different C. trachomatis strains may explain different strain-specific needs and phenotypic distinctions. This is further supported by the differential immunoreactivity to rPmpD and rPmpF of sera from patients infected with different strains. Furthermore, clinical E strains did not correlate with the E reference strain at the gene expression level, reinforcing the need for expansive studies of clinical strains